Rolling Casaer

"I lost my child, and my husband has suicided, leaving me alone, what should I do? Many times, I wanted to cry, but I told myself I couldn't cry and I couldn't fall down. Otherwise, who will help me find my child?"

"I'm 22 now, I have a family, I have kids, and I want so badly to know how my real parents are doing! I want to have a real mother so badly."

"It's been 15 years and I only feel like a father when I'm on the road to finding my child."

"14 years and 57 days gone, I have finally found my child, I will never have to look for my child again, the journey was too hard, too painful, finally it's over and I can start my life again."

"When you lose a child, a family falls apart. Not only is it financially ruined, it's mentally ruined too."


"Today is my 32nd birthday. How are you doing, my birth parents, whom I have never met? Have you thought about me over the years?"

Lost Children, Stolen Life.

Research background

Studies show that hundreds of thousands of human trafficking crimes are committed globally each year. Women and children account for more than 80 per cent of the world's trafficked persons. In China, trafficking crimes have been frequented since the 1960s, and despite repeated crackdowns by the public security authorities, they are still rampant.

Compared to women, children are less able to distinguish and resist, and are more vulnerable to abuse. Children are the future of human society and child trafficking cannot be tolerated in all human trafficking crimes, which not only cause serious harm to the families of those involved, but also have a negative impact on society. The issue of child trafficking has therefore become a common concern for society as a whole.

Data introduction

The main data is the existing public second-hand data crawled from the Chinese family tracing website "Baby Go Home". These data show information provided by people looking for their biological family. We mainly used the columns of date of birth, the time and location when trafficking. It also including current location and other information of the trafficked children. The last update of dataset is in November 2020.

In addition to the main data, we also collected and cleaned provincial and municipal data provincial and municipal data related to income, illiteracy, and unemployed, in preparation for analyzing the reasons behind the phenomenon.

analysis

Who?

Who is at risk of being trafficked

Trafficked children have different gender characteristics at different ages.

Before 2-year-old trafficked girls are more than boys, while for children aged 2 to 9, more boys are trafficked during this period than girls. According to word clouds, most of the missing places before the age of 1 are "hospitals". This is because under the pressure of traditional thinking and fertility policies, many children are abandoned in hospitals because of their gender or physical reasons, and then they are trafficked by human traffickers (Huang, 2017). For 2 to 9 years old, "train station" appeared the most. Scholars believe that these children have walk ability, but without clear memory (Tan, 2018). For traffickers who know the advantage of boys in the child trafficking market, this age group is the best choice for crime (Tan, 2018).

It should be noted that as the age continues to increase, the number of abducted females gradually exceeds that of males. This may be because of the demand for "child brides" in rural areas (Zhou and Chen, 2022).


Where?

Child trafficking flow network between provinces

Top two flows

  • Jiangsu → Shandong
  • Jiangsu → Henan

Areas with large internal flows & small external flows

  • Fujian
  • Sichuan
  • Guangdong

General flows direction

  • West → East
  • South → Centre

Where are the Clusters of Cases in Regions and Measure the Clusters by Spatial Autocorrelation?


Clustering Map
Local Moran's I Map

The Global Moran's I is 0.351:

The number of cases tends to be similar to the cities that are geographically nearby on the map.


Where have the Children been Found and Trafficked?



Hospital is the most common one;

Doorways:
The front of many places including the government, factories, homes, markets, and more.

When?

· The preference for boys has always been widespread in China, but the family planning policy implemented in the early 1980s has certainly exacerbated this phenomenon. the demand for male offspring, and the abandonment for female infants thus led to the formation of a large market for the trade in children. The number of trafficking cases reaching a peak around 1989.


· In the 1990s, the Chinese government launched a vigorous 'Daguai' (counter trafficking campaign) and the rampant child trafficking crime began to decline year on year.


· Since 2000, the number of trafficked children cases is dropping continually as the government has gradually loosened the restrictions on the number of births.

The seasonal variation of trafficked children cases is low, with a more even distribution across the seasons. But January has the most child missing cases, probably due to the Spring Festival when parents are more likely to go out with their children to crowded places, which means higher possibility to abduct children for human traffickers.

How?

How are the Children away from their Original Families and taken back from Foster Parents?

Two Categories in Flow In and Flow Out

How children Flow out:

  • Abandoned;
  • Giving Away;
  • Missing.
How children Flow in:

  • Public Adoption;
  • Private Adoption;
  • Picked up.

Why?

We analyse the relationship between child trafficking and economic/social characteristic in province level.

The first plot shows a positive relationship between wage and child trafficked in cases, which indicates that more children are trafficked into places with higher income.

The second plot shows a negative relationship between gini coefficient and child trafficked in cases, indicating that more children are trafficked into places with smaller income gap.

The third plot shows a negative relationship between unemployment rate and child trafficked in cases, which indicates that more children are trafficked into places with lower unemployment rate.

The fourth plot also shows a negative relationship between illiteracy rate and child trafficked in cases, indicating that more children are trafficked into places with lower illiteracy rate.

The results above are opposite to our hypothesis, and that maybe because of the ambiguity of the data. It only contains information about Current location of trafficked children , so we regard it as Places children trafficked in . However, it might be very likely that Current location of them are places they work and live after they grew up and left their adopted families, but not Places they trafficked in. Therefore, we should be critical about the results we got.

Conclusion

  • WHO: More girls trafficked in age before 2 and 10-17 , and more boys trafficked in age 2-9 .

  • WHERE: Child trafficking flows are generally from west to east and south to centre . Many children are found in hospitals and train stations.

  • WHEN: 1988-1990 period and January are the years and month of the peak of child trafficking.

  • HOW: Private adoption is the most common situation after a child being trafficked.

  • WHY: The reasons behind child trafficking phenomenon can be explained by different economic and social factors.

    • Write at the end

    Today, with the improvement of laws and policies, trafficking may have become a historical issue, but its remaining ethical issues still exists. Some children refuse to go back to their biological parents; the teenage girl who was abducted and married off was persuaded by her parents to return to the buyer; adoptive parents who were involving in illegal transactions use their children's rhetoric to incite public opinion to evade legal sanctions. The problem of trafficking exists in another form in every corner.

    Observing the essence of trafficking and subsequent problems, both originate from the traditional culture's restraint on women and the excessive obsession with clan reproduction, while child abduction is only one of the manifestations. Although through the woman's liberation movement, related problems have been greatly improved in the Chinese cities. But in rural areas, some hidden misogynies are still rampant, such as seeing everything related to women as inauspicious and vulnerable. In addition, rural men are also victims. Late marriages of man are often linked to lack of masculinity and dishonouring. These rules are continually perpetuated and enforced, becoming a hindrance to local gender liberation.

    China's economic poverty alleviation work in rural areas has achieved positive results, but poverty alleviation should not only be based on material and economic foundations, while ideological poverty alleviation will be a further work after that. Only when women and men are treated equally can the gap between urban and rural consciousness be filled and women and men can understand each other. Otherwise, when the other "birth restriction" comes, those abducted children will appear again.

    Advice such as strengthening legal penalties for buyers and sellers and building the search system for children have become the most vocal suggestions in Chinese public opinion. In addition, we believe that strengthening gender education and legal popularisation in rural areas and increasing the crackdown on extreme feudal ideology are one of the ways to eradicate gender rights issues including child trafficking.

    Limitations

    In Original Data

    • Messy of the Description Data

    • Possibly Inaccuracy of the Data

    • Lack of supplementary datasets in Regions

    In Analysis Process

    • Hard to Further Explain Under Some Circumstances

    • Consider more Geographical Segmentation rather than Culture

    • Different Wording in Each Person cause Potential Misunderstanding

    • Various Standards across different provinces in supplementary datasets

    Further work

    Data

    • Implement quality, quantity, and variety

    Analysis

    • Focus on smaller regional level (city/county…)
    • More integrated with the socio-cultural context for qualitative analysis
    • Follow-on impact on policy-making、urban and rural patterns
    • Individual case study

    Predictions

    • Potential inflow and outflow of children for trafficking in the future
    • Who will be next victims of trafficking?
    • Follow-on impact on policy-making, urban and rural patterns

    Presenting

    • Dynamic word cloud
    • Maps with timeline

    Children Trafficking

    Creators: Yiyang Dai, Jiayan Fan, Tong Li, Xinlei Yan, Yujun Yuan

    Group: Rolling Casaer